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This thesis investigates the design and evaluation of Large Language Model (LLM) agent assistants for industrial maintenance, developed in cooperation with SSAB. The study focuses on identifying what combinations of tools and architectures best serve the needs of maintenance technicians, with an emphasis on practical usability and factual correctness. Multiple agents were developed and compared,
